[The effect of smoking status upon occurrence of impaired fasting glucose or type 2 diabetes in Korean men]

Health effects associated with smoking: a Burden of Proof study

As a leading behavioral risk factor for numerous health outcomes, smoking is a major ongoing public health challenge. Although evidence on the health effects of smoking has been widely reported, few attempts have evaluated the dose-response relationship between smoking and a diverse range of health outcomes systematically and comprehensively. In the present study, we re-estimated the dose-response relationships between current smoking and 36 health outcomes by conducting systematic reviews up to 31 May 2022, employing a meta-analytic method that incorporates between-study heterogeneity into estimates of uncertainty. Among the 36 selected outcomes, 8 had strong-to-very-strong evidence of an association with smoking, 21 had weak-to-moderate evidence of association and 7 had no evidence of association. By overcoming many of the limitations of traditional meta-analyses, our approach provides comprehensive, up-to-date and easy-to-use estimates of the evidence on the health effects of smoking. These estimates provide important information for tobacco control advocates, policy makers, researchers, physicians, smokers and the public.

Systematic review with meta-analysis of the epidemiological evidence relating smoking to type 2 diabetes

BACKGROUND

Evidence relating tobacco smoking to type 2 diabetes has accumulated rapidly in the last few years, rendering earlier reviews considerably incomplete.

AIM

To review and meta-analyse evidence from prospective studies of the relationship between smoking and the onset of type 2 diabetes.

METHODS

Prospective studies were selected if the population was free of type 2 diabetes at baseline and evidence was available relating smoking to onset of the disease. Papers were identified from previous reviews, searches on Medline and Embase and reference lists. Data were extracted on a range of study characteristics and relative risks (RRs) were extracted comparing current, ever or former smokers with never smokers, and current smokers with non-current smokers, as well as by amount currently smoked and duration of quitting. Fixed- and random-effects estimates summarized RRs for each index of smoking overall and by various subdivisions of the data: Sex; continent; publication year; method of diagnosis; nature of the baseline population (inclusion/exclusion of pre-diabetes); number of adjustment factors; cohort size; number of type 2 diabetes cases; age; length of follow-up; definition of smoking; and whether or not various factors were adjusted for. Tests of heterogeneity and publication bias were also conducted.

RESULTS

The literature searches identified 157 relevant publications providing results from 145 studies. Fifty-three studies were conducted in Asia and 53 in Europe, with 32 in North America, and seven elsewhere. Twenty-four were in males, 10 in females and the rest in both sexes. Fifteen diagnosed type 2 diabetes from self-report by the individuals, 79 on medical records, and 51 on both. Studies varied widely in size of the cohort, number of cases, length of follow-up, and age. Overall, random-effects estimates of the RR were 1.33 [95% confidence interval (CI): 1.28-1.38] for current vs never smoking, 1.28 (95%CI: 1.24-1.32) for current vs non-smoking, 1.13 (95%CI: 1.11-1.16) for former vs never smoking, and 1.25 (95%CI: 1.21-1.28) for ever vs never smoking based on, respectively, 99, 156, 100 and 100 individual risk estimates. Risk estimates were generally elevated in each subdivision of the data by the various factors considered (exceptions being where numbers of estimates in the subsets were very low), though there was significant (P < 0.05) evidence of variation by level for some factors. Dose-response analysis showed a clear trend of increasing risk with increasing amount smoked by current smokers and of decreasing risk with increasing time quit. There was limited evidence of publication bias.

CONCLUSION

The analyses confirmed earlier reports of a modest dose-related association of current smoking and a weaker dose-related association of former smoking with type 2 diabetes risk.

The 2016 global and national burden of diabetes mellitus attributable to PM2·5 air pollution

BACKGROUND

PM_2·5 air pollution is associated with increased risk of diabetes; however, a knowledge gap exists to further define and quantify the burden of diabetes attributable to PM_2·5 air pollution. Therefore, we aimed to define the relationship between PM_2·5 and diabetes. We also aimed to characterise an integrated exposure response function and to provide a quantitative estimate of the global and national burden of diabetes attributable to PM_2·5.

METHODS

We did a longitudinal cohort study of the association of PM_2·5 with diabetes. We built a cohort of US veterans with no previous history of diabetes from various databases. Participants were followed up for a median of 8·5 years, we and used survival models to examine the association between PM_2·5 and the risk of diabetes. All models were adjusted for sociodemographic and health characteristics. We tested a positive outcome control (ie, risk of all-cause mortality), negative exposure control (ie, ambient air sodium concentrations), and a negative outcome control (ie, risk of lower limb fracture). Data for the models were reported as hazard ratios (HRs) and 95% CIs. Additionally, we reviewed studies of PM_2·5 and the risk of diabetes, and used the estimates to build a non-linear integrated exposure response function to characterise the relationship across all concentrations of PM_2·5 exposure. We included studies into the building of the integrated exposure response function if they scored at least a four on the Newcastle-Ottawa Quality Assessment Scale and were only included if the outcome was type 2 diabetes or all types of diabetes. Finally, we used the Global Burden of Disease study data and methodologies to estimate the attributable burden of disease (ABD) and disability-adjusted life-years (DALYs) of diabetes attributable to PM_2·5 air pollution globally and in 194 countries and territories.

FINDINGS

We examined the relationship of PM_2·5 and the risk of incident diabetes in a longitudinal cohort of 1 729 108 participants followed up for a median of 8·5 years (IQR 8·1-8·8). In adjusted models, a 10 μg/m³ increase in PM_2·5 was associated with increased risk of diabetes (HR 1·15, 95% CI 1·08-1·22). PM_2·5 was associated with increased risk of death as the positive outcome control (HR 1·08, 95% CI 1·03-1·13), but not with lower limb fracture as the negative outcome control (1·00, 0·91-1·09). An IQR increase (0·045 μg/m³) in ambient air sodium concentration as the negative exposure control exhibited no significant association with the risk of diabetes (HR 1·00, 95% CI 0·99-1·00). An integrated exposure response function showed that the risk of diabetes increased substantially above 2·4 μg/m³, and then exhibited a more moderate increase at concentrations above 10 μg/m³. Globally, ambient PM_2·5 contributed to about 3·2 million (95% uncertainty interval [UI] 2·2-3·8) incident cases of diabetes, about 8·2 million (95% UI 5·8-11·0) DALYs caused by diabetes, and 206 105 (95% UI 153 408-259 119) deaths from diabetes attributable to PM_2·5 exposure. The burden varied substantially among geographies and was more heavily skewed towards low-income and lower-to-middle-income countries.

INTERPRETATION

The global toll of diabetes attributable to PM_2·5 air pollution is significant. Reduction in exposure will yield substantial health benefits.

FUNDING

US Department of Veterans Affairs.

The impact of smoking on the development of diabetes and its complications

Diabetes is one of the most common metabolic disorders and emerges secondary to an interaction between genetic, environmental and lifestyle factors. This work provides an overview of the impact of smoking on the development of vascular complications in this condition and also provides an overview of the potential role of smoking in predisposition to diabetes. There are many studies documenting the impact of smoking on health (not focused on patients with diabetes), suggesting that the health exposure in these individuals is at least comparable to that observed in the general population. Distinct studies of smoking in patients with diabetes have unambiguously confirmed an increased prevalence and a higher risk of early death associated with the development of macrovascular complications. Smoking is also associated with premature development of microvascular complications and may contribute to the pathogenesis of type 2 diabetes. It has been shown that smoking is a predictor of the progression of glucose intolerance at both the transition from normoglycaemia to impaired glucose tolerance status and the increased risk of developing diabetes. The mechanisms explaining the relationship between smoking and the development of diabetes are not fully understood, although a number of hypotheses have been put forward. Current evidence indicates that smoking cessation is not only important to prevent macrovascular complications in diabetes, but also has a role in limiting microvascular disease and may also facilitate glycaemic management in this condition.

Association of passive and active smoking with incident type 2 diabetes mellitus in the elderly population: the KORA S4/F4 cohort study

Active smoking is a risk factor for type 2 diabetes (T2DM), but it is unclear whether exposure to environmental tobacco smoke (ETS) is also associated with T2DM. The effect of passive and active smoking on the 7-year T2DM incidence was investigated in a population-based cohort in Southern Germany (KORA S4/F4; 1,223 subjects aged 55-74 years at baseline in 1999-2001, 887 subjects at follow-up). Incident diabetes was identified by oral glucose tolerance tests or by validated physician diagnoses. Among never smokers, subjects exposed to ETS had an increased diabetes risk in the total sample (odds ratio (OR) = 2.5; 95% confidence interval (CI): 1.1, 5.6) and in a subgroup of subjects having prediabetes at baseline (OR = 4.4; 95% CI: 1.5, 13.4) after adjusting for age, sex, parental diabetes, socioeconomic status, and lifestyle factors. Active smoking also had a statistically significant effect on diabetes incidence in the total sample (OR = 2.8; 95% CI: 1.3, 6.1) and in prediabetic subjects (OR = 7.8; 95% CI: 2.4, 25.7). Additional adjustment for components of the metabolic syndrome including waist circumference did not attenuate any of these associations. This study provides evidence that both passive and active smoking is associated with T2DM.

Diabetes and impaired fasting glucose in Mongolian population, Inner Mongolia, China

AIMS

The aims of this study is to assess the prevalence of diabetes and IFG and compare the risk factors between diabetes and IFG in the Mongolian population, China.

METHODS

Data on demographic characteristics, lifestyle risk factors, family history of hypertension, medical history and fasting plasma glucose were obtained and analyzed for all individuals.

RESULTS

Total 2589 Mongolians aged 20 years or more were recruited as study subjects. The overall prevalence of diabetes and IFG was 3.7% (males 3.9%; females 3.5%) and 18.5% (males 17.7%; females 19.0%), respectively. Multivariate logistic analysis showed that diabetes was significantly associated with age (odds ratio: 1.26), overweight (1.86), high triglycerides (1.96), family history of hypertension (1.86), heart rate (1.05) and high C-reactive protein (3.59), and IFG significantly associated with age (odds ratio: 1.11), low high-density lipoprotein-cholesterol (1.80), family history of hypertension (1.60), heart rate (1.03) and high C-reactive protein (2.73).

CONCLUSIONS

IFG were common among Mongolian people living in the northeast of China. IFG has partly same risk factors as diabetes, and prevalence of some cardiovascular risk factors and number of risk factor in diabetes were higher than that in IFG.